| 1057 |
Centers for Disease Control and Prevention |
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Revised Surveillance Case Definition for HIV Infection - United States, 2014 |
Prepared by. |
| HIV antibody test | 0.694189 |
| immunofluorescence HIV antibody | 0.523179 |
| criteria | 0.565914 |
| indeterminate HIV infection | 0.525471 |
| York State Department | 0.529482 |
| HIV NAT | 0.523528 |
| antibody test result | 0.537645 |
| CDC Staff Members | 0.522363 |
| initial HIV test | 0.534083 |
| New York City | 0.566739 |
| HIV infection diagnosis | 0.528998 |
| HIV-2 infection | 0.526507 |
| CD4+ T-lymphocyte count | 0.53272 |
| HIV infection stages | 0.559755 |
| negative HIV test | 0.540023 |
| indeterminate HIV test | 0.547081 |
| acute HIV infection | 0.583665 |
| HIV surveillance | 0.524499 |
| supplemental HIV antibody | 0.525705 |
| early HIV infection | 0.623015 |
| negative HIV antibody | 0.556421 |
| opportunistic illnesses | 0.518145 |
| public health | 0.593865 |
| HIV surveillance programs | 0.523848 |
|
| positive HIV test | 0.553598 |
| New York | 0.673 |
| test results | 0.605764 |
| New Jersey Department | 0.52381 |
| HIV test result | 0.587213 |
| laboratory criteria | 0.519996 |
| pediatric HIV infection | 0.52959 |
| laboratory evidence | 0.519137 |
| New York State | 0.529817 |
| new HIV testing | 0.524201 |
| HIV test | 0.619336 |
| CD4+ T-lymphocyte | 0.616106 |
| HIV infection burden | 0.544932 |
| opportunistic illness | 0.526126 |
| San Francisco | 0.525523 |
| York City Department | 0.566506 |
| undifferentiated HIV infection | 0.524868 |
| surveillance case definition | 0.519404 |
| case definition | 0.578275 |
| initial HIV antibody | 0.52366 |
| Richard M. Selik | 0.526948 |
| HIV test results | 0.525513 |
| supplemental HIV test | 0.530792 |
|
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| 2949 |
Centers for Disease Control and Prevention |
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Mariano's Story - Real Stories - Tips from Former Smokers - Smoking & Tobacco Use |
The story of Mariano, a former smoker who almost had a heart attack and is featured in CDC's Tips from Former Smokers campaign. |
| blood pressure | 0.498629 |
| cigarette | 0.274536 |
| chance | 0.3699 |
| hospitalization | 0.281237 |
| lives | 0.27441 |
| morning feeling | 0.542974 |
| blood vessels | 0.487905 |
| Mariano | 0.854599 |
| video | 0.261207 |
| good. | 0.264917 |
|
| way | 0.264658 |
| food | 0.263399 |
| life | 0.261815 |
| doctor | 0.267607 |
| Illinois | 0.274341 |
| Smokers® campaign | 0.489585 |
| heart surgery. | 0.471762 |
| sweating. | 0.262131 |
| open heart surgery | 0.976235 |
| CDC’s Tips | 0.498436 |
|
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| 6842 |
Centers for Disease Control and Prevention |
Html |
en |
National Kidney Month - March 2012 |
Persons using assistive technology might not be able to fully access information in this file. For assistance, please send e-mail to: mmwrq@cdc.gov. |
| mmwrq@cdc.gov. | 0.372623 |
| Kidney Diseases | 0.44817 |
| preliminary data | 0.366211 |
| major risk factors | 0.414856 |
| Kochanek KD | 0.364476 |
| Human Services | 0.415147 |
| assistive technology | 0.372432 |
| U.S. Department | 0.41381 |
| MMWR HTML versions | 0.410538 |
| Patient awareness | 0.36211 |
| kidney disease prevention | 0.640601 |
| electronic PDF version | 0.410641 |
| Murphy SL | 0.359849 |
| early detection | 0.370958 |
| National Institutes | 0.364676 |
| Contact GPO | 0.370298 |
| Xu JQ | 0.364929 |
| commercial sources | 0.359413 |
| end-stage renal disease | 0.437664 |
| Boulware LE | 0.364844 |
| current prices | 0.358908 |
| National Chronic Kidney | 0.537827 |
| Disease Fact Sheet | 0.438352 |
| National Kidney | 0.482539 |
|
| original paper copy | 0.407729 |
| chronic kidney disease | 0.988941 |
| United States | 0.490473 |
| original MMWR paper | 0.414639 |
| U.S. Government Printing | 0.412858 |
| kidney failure | 0.49583 |
| partner agencies | 0.361708 |
| Kidney Disease Initiative | 0.524348 |
| MMWR readers | 0.362905 |
| National Institute | 0.366807 |
| Natl Vital Stat | 0.418876 |
| cardiovascular disease | 0.382879 |
| subject line | 0.371437 |
| annual data report | 0.414405 |
| U.S. adults | 0.37131 |
| typeset documents | 0.360085 |
| trade names | 0.35945 |
| national CKD surveillance | 0.483298 |
| Arch Intern Med | 0.413282 |
| official text | 0.359584 |
| non-CDC sites | 0.35925 |
| Plantinga LC | 0.363733 |
| high blood pressure | 0.419116 |
| et al | 0.35926 |
|
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| 8089 |
Centers for Disease Control and Prevention |
Html |
en |
Preventing Chronic Disease - CDC: Volume 10, 2013: 12_0145e |
Volume 10 — February 14, 2013. |
| citation | 0.20082 |
| academic degree | 0.424406 |
| Human Services | 0.411826 |
| Prev Chronic Dis | 0.921852 |
| Better Health Policy | 0.699734 |
| U.S. Department | 0.413251 |
| Meda Pavkov | 0.603457 |
| Disease Control | 0.403522 |
|
| Sanford Garfield | 0.497558 |
| Public Health Service | 0.670912 |
| affiliated institutions | 0.406125 |
| Natural Experiments | 0.442373 |
| Meda E. Pavkov | 0.871381 |
| Diabetes Prevention | 0.437127 |
| byline | 0.250916 |
|
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| 8859 |
Centers for Disease Control and Prevention |
Html |
en |
Frequently Asked Questions | West Nile Virus |
Information on West Nile Virus. Provided by the U.S. Centers for Disease Control and Prevention. |
| MPEG | 0.741242 |
| site | 0.541063 |
| PDF | 0.544429 |
|
|
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| 11062 |
Centers for Disease Control and Prevention |
Html |
en |
Preventing Chronic Disease | Socioecologic Factors as Predictors of Readiness for Self-Management and Transition, Medication Adherence, and Health Care Utilization Among Adolescents and Young Adults With Chronic Kidney Disease - CDC |
The objective of our study was to determine the socioecologic factors that predict readiness for self-management and transition from pediatric to adult health care services, adherence to taking medications, and health care utilization among adolescents and young adults with chronic kidney disease. |
| North Carolina | 0.429033 |
| UNC TRxANSITION scale | 0.367972 |
| regression analyses | 0.364493 |
| trained research assistant | 0.373911 |
| health insurance | 0.374147 |
| observation period | 0.367608 |
| emergency department visits | 0.469983 |
| health care provider | 0.36433 |
| total TRxANSITION score | 0.369959 |
| medication adherence | 0.686872 |
| significant positive predictor | 0.378165 |
| private health insurance | 0.372913 |
| number | 0.398635 |
| medications | 0.403494 |
| negative value | 0.356945 |
| private insurance | 0.424381 |
| individualized education plan | 0.479027 |
| physician-reported adherence rating | 0.364618 |
| physician-reported medication adherence | 0.480958 |
| health care services | 0.423212 |
| adult-focused health care | 0.366941 |
| emergency department | 0.526156 |
| insurance status | 0.43581 |
| public health insurance | 0.360549 |
|
| disease self-management subscale | 0.360264 |
| IEP | 0.389011 |
| young adults | 0.430825 |
| positive value | 0.358506 |
| health care utilization | 0.989675 |
| study | 0.40941 |
| chronic kidney disease | 0.409228 |
| TRxANSITION scale | 0.381246 |
| readiness | 0.392364 |
| chronic health conditions | 0.356577 |
| pediatric patients | 0.356717 |
| Health Insurance Portability | 0.364679 |
| emergency health care | 0.360763 |
| care] providers. | 0.364402 |
| health care transition | 0.3938 |
| participants | 0.4721 |
| pharmacy refill records | 0.370516 |
| disease self-management | 0.382131 |
| UNC Kidney Center | 0.365306 |
| self-management | 0.419516 |
| 504 plan had significantly more emergency | 0.38131 |
| Chapel Hill | 0.356506 |
| socioecologic factors | 0.626082 |
| public insurance | 0.468727 |
|
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| 11590 |
Centers for Disease Control and Prevention |
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Disease Detective: Dominique - CDC Responds to the 2014 Ebola Outbreak |
CDC works 24/7 saving lives, protecting people from health threats, and saving money to have a more secure nation. A US federal agency, CDC helps make the healthy choice the easy choice by putting science and prevention into action. CDC works to help people live longer, healthier and more productive lives. |
| high school | 0.562818 |
| CDC | 0.724102 |
| main roles | 0.585557 |
| Epi-Info | 0.462402 |
| young woman | 0.560018 |
| Ebola outbreak | 0.656392 |
| MSF Treatment Center | 0.758384 |
| good data management | 0.739754 |
| wonderful advocate | 0.564806 |
| World Health Organization | 0.745218 |
| CDC epidemiologists | 0.698041 |
| public health partners | 0.740175 |
| patients | 0.453751 |
| public health emergencies | 0.78304 |
| improved contact tracing | 0.740394 |
| extraordinary efforts | 0.562939 |
| predominantly French-speaking country | 0.757964 |
| public meetings | 0.569684 |
| oldest school | 0.562159 |
| long nights | 0.568815 |
| Dominique | 0.753705 |
| data entry | 0.591794 |
| prior deployments | 0.607882 |
| data management | 0.926942 |
| Guinea | 0.466568 |
|
| CDC’s partners | 0.653288 |
| Sierra Leone | 0.574418 |
| crucial tool | 0.586719 |
| current puzzle | 0.572374 |
| vital need | 0.583575 |
| health worker | 0.575183 |
| Pierre Rollin | 0.57159 |
| France | 0.459795 |
| hospital | 0.459075 |
| current outbreak | 0.617657 |
| CDC staff | 0.7125 |
| cases | 0.460524 |
| statistical analysis program | 0.737708 |
| medicine | 0.467754 |
| unique combination | 0.586405 |
| sick person | 0.566492 |
| medical student | 0.562111 |
| best things | 0.562701 |
| viral hemorrhagic fevers | 0.723325 |
| important pieces | 0.580613 |
| West Africa | 0.60451 |
| young man | 0.568819 |
| personal note | 0.56173 |
| contacts | 0.460938 |
|
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Non-Polio Enterovirus | Prevention and Treatment Non-Polio Enterovirus Infection | Picornavirus | CDC |
You can help protect yourself and others from non-polio enterovirus infections by washing your hands and disinfecting surfaces. There is no specific treatment for non-polio enterovirus infection. |
| Enterovirus D68 | 0.465573 |
| prevention steps | 0.33056 |
| non-polio enterovirus infection | 0.969772 |
| non-polio enteroviruses | 0.472941 |
| non-polio enterovirus infections | 0.570896 |
| hospitalization | 0.232207 |
| to— | 0.223874 |
| illnesses | 0.225829 |
| health care provider | 0.41429 |
|
| specific treatment | 0.316386 |
| supportive treatment | 0.319131 |
| best way | 0.330359 |
| people | 0.269956 |
| symptoms | 0.273584 |
| vaccine | 0.229284 |
| over-the-counter cold medications | 0.431322 |
| drinking enough water | 0.321593 |
|
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| 15959 |
Centers for Disease Control and Prevention |
Html |
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Halloween Health and Safety Tips |
Family health information from the Centers for Disease Control and Prevention (CDC) |
| possible skin | 0.715808 |
| obstacles | 0.541038 |
| Check | 0.541658 |
| festivities fun | 0.752027 |
| trick-or-treat time | 0.723234 |
| tips | 0.541626 |
| healthy snacks | 0.744097 |
| safety | 0.541811 |
| eye irritation | 0.729109 |
| Wear well-fitting masks | 0.884607 |
| Lower your risk | 0.71102 |
| eye injury | 0.710989 |
| walking areas | 0.703452 |
| landings | 0.541056 |
| knives | 0.540164 |
| strangers | 0.600612 |
| party games | 0.695999 |
| Fasten reflective tape | 0.929113 |
| fun times | 0.744676 |
| sturdy tables | 0.718738 |
| luminaries | 0.612024 |
| factory-wrapped treats | 0.852835 |
| trick-or-treaters | 0.748559 |
| parties | 0.542226 |
| party guests | 0.73987 |
|
| adult | 0.579079 |
| drivers | 0.575835 |
| flame-resistant costumes | 0.77028 |
| low-calorie treats | 0.845115 |
| daily dose | 0.704196 |
| well-lit houses | 0.707014 |
| sidewalks | 0.544879 |
| small children | 0.695463 |
| hazards | 0.539796 |
| decorative contact lenses | 0.893003 |
| Swords | 0.544576 |
| small area | 0.72268 |
| Fall celebrations | 0.752771 |
| flashlight | 0.551373 |
| yummy treats | 0.921523 |
| healthier treats | 0.836003 |
| walkways | 0.543245 |
| homemade treats | 0.845738 |
| groups | 0.540869 |
| physical activity | 0.934311 |
| costume accessories | 0.743367 |
| treats | 0.931801 |
| lit candles | 0.715593 |
| candle-lit jack o’lanterns | 0.902891 |
|
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| 16095 |
Centers for Disease Control and Prevention |
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Prescribing Data |
null |
| opioid pain relievers | 0.877434 |
| opioid prescriptions | 0.371721 |
| chronic pain | 0.497219 |
| opioid prescription prescriptions | 0.530773 |
| United States | 0.222699 |
| prescription opioid overdose | 0.732303 |
| Tool Interactive mapping | 0.23285 |
| mapping tool | 0.218556 |
| pain management | 0.279309 |
| primary care settings | 0.268146 |
| Wide-ranging Online Data | 0.245142 |
|
| primary care providers | 0.278643 |
| Opioid Drug Mapping | 0.418122 |
| StatisticsThis web site | 0.23512 |
| highest risk | 0.267011 |
| opioid prescribing | 0.407303 |
| pain medicine | 0.301236 |
| prescription opioids | 0.976919 |
| non-cancer pain | 0.304681 |
| primary care | 0.282188 |
| public health professionals | 0.251891 |
| health care providers | 0.497777 |
|
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